A method for establishing a crystal plasticity constitutive model under thermomechanical fatigue conditions

Abstract

The present invention discloses a method for establishing a crystal plasticity constitutive model under thermomechanical fatigue conditions, which belongs to the technical field of thermomechanical fatigue analysis of materials, and includes the following steps: deriving the constitutive theory of crystal plasticity under thermomechanical fatigue; establishing a finite element simulation model and applying boundary conditions; obtaining the numerical values ​​of various material parameters in crystal plasticity under thermomechanical fatigue conditions through simulation analysis; writing corresponding UMAT subroutines based on the constitutive theory of crystal plasticity under thermomechanical fatigue; carrying out simulation analysis of crystal plasticity constitutive model under thermomechanical fatigue, and comparing the simulation results with the test results. The model established by the present invention can more accurately simulate the influence of the interaction of cyclic mechanical loads and thermal loads to which the material is subjected under service conditions, greatly improving the prediction accuracy of the mechanical response behavior of the material under thermal-mechanical coupling conditions, and helping to better predict the fatigue failure behavior of the material.

Description

Technical Field

[0001] The invention mainly relates to the technical field of material thermomechanical fatigue analysis, and specifically to a method for establishing a crystal plastic constitutive model under thermomechanical fatigue conditions. Background Art

[0002] With the further development of modern aviation industry, variable cycle engines can realize the conversion of turbofan / turbojet working modes through the switch of mode switching valve and duct ejector, so that the engine has good overall performance in subcruise, economic supercruise and high-speed flight. Hot end components such as turbine disks are not only affected by alternating loads during service, but also by thermal loads caused by strong temperature transients, making the thermomechanical fatigue problem of disk materials particularly prominent. In order to predict the thermomechanical fatigue failure behavior of materials, it is necessary to accurately describe the mechanical response behavior of materials under thermomechanical fatigue. Traditional modeling methods are usually based on the macroscopic mechanical theoretical framework of materials (such as elastic-plastic and viscoplastic constitutive models), which cannot reflect the influence of grain-level microstructure on fatigue failure behavior, and the prediction accuracy is not high.

[0003] In the field of crystal plasticity, by establishing a three-dimensional model that can reflect the grain size and grain orientation and considering the microstructure of the material, the prediction accuracy of the mechanical response behavior of the material can be significantly improved. For example, a method for predicting the mechanical properties of metal materials considering microtexture is disclosed in the patent with application publication number CN114034609 A. It considers the two strengthening mechanisms of dislocation strengthening and fine grain strengthening in metal materials based on the crystal plasticity constitutive framework, establishes a crystal plasticity constitutive model considering dislocation strengthening and fine grain strengthening, uses the characteristic size of the grain slip system to replace the average grain size to describe the microstructure of complex texture, applies the characteristic size of the grain slip system to the above-mentioned crystal plasticity constitutive model, and further establishes an improved crystal plasticity constitutive model considering dislocation strengthening, fine grain strengthening and grain structure morphology. By improving the crystal plasticity constitutive model, the relationship between the geometric morphology of the material and the mechanical properties is established, and the micro-nano mechanical properties of materials with different microtextures are accurately characterized, thereby improving the prediction accuracy of the mechanical properties of metal materials. However, the material analysis methods that consider microtextures such as the aforementioned ones have the following problems: most of the existing crystal plasticity models only consider the influence of mechanical cyclic loads, but do not consider the influence of thermal environment, and thus cannot accurately describe the mechanical response behavior of materials under thermomechanical fatigue. Summary of the invention

[0004] The technical solution of the present invention aims at the technical problem that the existing technical solutions are too single, and provides a solution that is significantly different from the existing technologies. It mainly provides a method for establishing a crystal plastic constitutive model under thermomechanical fatigue conditions, which is used to solve problems such as accurately describing the mechanical response behavior of materials under thermomechanical fatigue, and helps to better predict the fatigue failure behavior of materials and improve the prediction accuracy of the mechanical properties of materials.

[0005] The technical solution adopted by the present invention to solve the above technical problems is:

[0006] A method for establishing a crystal plasticity constitutive model under thermomechanical fatigue conditions comprises the following steps:

[0007] S1. Derive the constitutive theory of crystal plasticity under thermomechanical fatigue;

[0008] S2, establish a finite element simulation model and apply boundary conditions;

[0009] S3. Obtain the values ​​of various material parameters in crystal plasticity under thermomechanical fatigue conditions through simulation analysis;

[0010] S4, based on the crystal plasticity constitutive theory under thermomechanical fatigue derived in step S1, write the corresponding UMAT subroutine;

[0011] S5. Based on steps S2, S3 and S4, a simulation analysis of crystal plasticity constitutive model under thermomechanical fatigue is carried out, and finally the simulation results are compared with the test results to verify the accuracy of the simulation results.

[0012] Furthermore, in step S1, three parts including elastic deformation gradient, plastic deformation gradient and thermal deformation gradient are comprehensively considered.

[0013] Furthermore, the specific process of step S1 is:

[0014] S11, deformation gradient F can be decomposed into three parts: elastic deformation gradient, plastic deformation gradient and thermal deformation gradient, namely:

[0015] F=F e F θ F p

[0016] where F e is the elastic deformation gradient, F θ is the thermal deformation gradient, F p is the plastic deformation gradient;

[0017] S12. According to the plastic deformation gradient of the slip system and Schmid's law, we can get:

[0018]

[0019] in is the shear strain rate of slip system α, is the contravariant tensor, s α is the normal direction of the slip surface of the slip system α, m α is the slip direction of the slip system α;

[0020] S13. Combined with the thermal expansion coefficient measured in the test, it can be obtained that:

[0021]

[0022] in, is the contravariant tensor, is the temperature change rate, ρ is the second-order tensor form of the thermal expansion coefficient;

[0023] S14. According to the power-rate hardening law, we can get:

[0024]

[0025] Among them, τ α is the shear stress of the slip system α, X α is the α back stress of the slip system, g α is the α hardening strength of the slip system, is the reference shear strain rate;

[0026] S15. According to the Voce type isotropic hardening model, we can get:

[0027]

[0028] Among them, τ0, τ s , g0 is the material parameter, is the rate of change of hardening modulus, γ is the shear strain, q is the cyclic soft hardening control parameter, β is the reference slip system, and δ is the Kronecker symbol;

[0029] S16. According to the AF type kinematic hardening model, it can be obtained that:

[0030]

[0031] in, is the back stress change rate, C and D are material parameters.

[0032] Furthermore, the specific process of step S2 is:

[0033] S21. In the dream3D software, import the grain orientation and grain size of the target material, consider both the calculation efficiency and the accuracy of the calculation results, select the finite element model size and the grid unit size, and generate the input file of the three-dimensional representative volume unit;

[0034] S22, integrate and import the input files into the abaqus finite element, and use the python script to input material parameters and periodic boundary conditions;

[0035] S23. Apply fixed constraints to the three vertices of the three-dimensional representative volume unit, apply a displacement load corresponding to the cycle to another vertex, and apply a uniformly changing cyclic temperature to the entire model.

[0036] Furthermore, at least one of an optical microscope, a scanning electron microscope, and an electron backscatter microscope is used in advance to analyze and obtain the grain orientation and grain size of the target material.

[0037] Furthermore, the specific process of step S3 is:

[0038] S31, according to the thermomechanical fatigue temperature range, perform isothermal fatigue test, by continuously adjusting various parameters of crystal plasticity, compare the simulation results at various temperatures with the test results at corresponding temperatures, until the average error reaches the requirement, at which time each parameter is the crystal plasticity parameter at the corresponding temperature;

[0039] S32. In order to obtain the magnitude of the temperature variation of various parameters under thermomechanical fatigue conditions, the elastic tensor C ij Expressed as a function of temperature T:

[0040] E=f(T)

[0041] K ij =C ij / E

[0042] Where E is the elastic modulus, f(T) is the temperature-dependent linear function, and K ij are the parameters obtained for the fitting;

[0043] S33. The relationship between the power-rate hardening model parameter n and the temperature T is as follows:

[0044]

[0045] Among them, η f and μ f are parameters related to the elastic tensor, k is the Boltzmann constant, and A2 is the fitting parameter;

[0046] Among the S34 and Voce type anisotropic parameters, the relationship between each parameter and temperature is as follows:

[0047]

[0048] Among them, χ(T), φ(T), and ψ(T) are temperature-related linear functions, which are obtained by fitting. is the material parameter at reference temperature;

[0049] S35. For the back stress parameter C / D, it can also be expressed as an exponential correlation function. The specific formula is as follows:

[0050]

[0051] D=A4exp(υ(T))+B4

[0052] in, υ(T) is also a linear function related to temperature, and A3-A4 and B3-B4 are parameters obtained by fitting;

[0053] S36. Substitute the numerical values ​​of the crystal plastic material parameters obtained by simulation at different temperatures in S31 into S32-S35 for fitting, so as to obtain the function size of each parameter related to temperature under thermomechanical fatigue conditions.

[0054] Specifically, in step S31, the condition for the average error to meet the requirement is that the average error is less than 10%.

[0055] Furthermore, the specific process of step S4 is:

[0056] S41. According to the microstructure of the target material, corresponding parameters are used to describe its elastic deformation behavior. By adjusting the size of these parameters, the elastic section results of static stretching in the simulation results are controlled. Static stretching simulation and experiments are performed at different temperatures. The static stretching simulation results and test results are compared to determine the appropriate value parameters. The initial elastic tensor at the initial temperature is compiled into the UMAT subroutine.

[0057] S42, setting the time increment step size, calculating the strain increment Δε and the local elastic tensor corresponding to the time Δt, and counting the slip system direction s and the slip surface normal vector m;

[0058] S43, calculating the initial solution of the shear strain increment Δγ within the time Δt by using the given initial parameter values;

[0059] S44, use the Newton-Raphson method to perform iterative calculations, and determine whether Δγ converges in UMAT. If not, update the material parameters and continue the iterative calculations; if converged, obtain the analytical solution size γ t+Δt After that, the next time increment t = (1 + n) Δt is entered to continue the calculation until the incremental step reaches the set step size, that is, t = t step Stop calculation.

[0060] Furthermore, the specific process of step S5 is:

[0061] The crystal plastic material parameters under the thermomechanical fatigue conditions in step S3 are assigned to the model established in step S2 in abaqus. Combined with the UMAT subroutine written in step S4 as the calculation basis of abaqus, a simulation analysis of the crystal plastic constitutive under thermomechanical fatigue is carried out. The simulation results are compared with the experimental results to verify the accuracy of the simulation results.

[0062] Compared with the prior art, the present invention has the following beneficial effects:

[0063] The present invention provides a method for establishing a finite element model of crystal plasticity under thermomechanical fatigue conditions. Compared with the traditional crystal plasticity model that only considers the influence of mechanical cyclic loads, the present invention introduces a thermal expansion deformation gradient term into the traditional crystal plasticity model to simulate its thermomechanical fatigue cyclic deformation behavior, and verifies it with the hysteresis loop results obtained in the experiment. Therefore, the model established by the present invention can more accurately simulate the influence of the interaction of cyclic mechanical loads and thermal loads on the material under service conditions, greatly improving the prediction accuracy of the mechanical response behavior of the material under thermal-mechanical coupling conditions.

[0064] The present invention will be explained in detail below with reference to the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 A flow chart of a constitutive modeling method of crystal plasticity under thermomechanical fatigue conditions of the present invention;

[0066] Figure 2 Obtain IPF diagram of grain structure in specific area of ​​material for EBSD analysis;

[0067] Figure 3 is the established three-dimensional representative volume unit;

[0068] Figure 4 The simulation results of low cycle fatigue at different temperatures;

[0069] Figure 5 Write methods for UMAT subroutines;

[0070] Figure 6 The static stretching simulation results and experimental results at different temperatures are shown in the figure;

[0071] Figure 7 This is a comparison chart between the thermomechanical fatigue simulation results and the test results under the same phase;

[0072] Figure 8 This is a comparison chart between the thermomechanical fatigue simulation results and the test results under the opposite phase. DETAILED DESCRIPTION

[0073] To facilitate understanding of the present invention, the present invention will be described more comprehensively below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings, but the present invention can be implemented in different forms and is not limited to the embodiments described in the text. On the contrary, these embodiments are provided to make the content disclosed in the present invention more thorough and comprehensive.

[0074] Example 1: Please refer to the attached Figure 1 , for the powder high temperature alloy material for wheel disc, a method for establishing a crystal plastic constitutive model under thermomechanical fatigue conditions includes the following steps:

[0075] Step 1, derive the constitutive theory of crystal plasticity under thermomechanical fatigue;

[0076] The specific process of step 1 is as follows:

[0077] S11, deformation gradient F can be decomposed into three parts: elastic deformation gradient, plastic deformation gradient and thermal deformation gradient, namely:

[0078] F=F e F θ F p

[0079] where F e is the elastic deformation gradient, F θ is the thermal deformation gradient, F p is the plastic deformation gradient.

[0080] S12. According to the plastic deformation gradient of the slip system and Schmid's law, we can get:

[0081]

[0082] in, is the shear strain rate of slip system α, is the contravariant tensor, s α is the normal direction of the slip surface of the slip system α, m α is the slip direction of the slip system α.

[0083] S13. The thermal expansion coefficient measured by the combined test (thermal expansion test in the range of 500-800°C) can be obtained:

[0084]

[0085] in, is the contravariant tensor, is the temperature change rate, and ρ is the second-order tensor form of the thermal expansion coefficient.

[0086] S14. According to the power-rate hardening law, we can get:

[0087]

[0088] where τ α is the shear stress of the slip system α, X α is the α back stress of the slip system, g α is the α hardening strength of the slip system, is the reference shear strain rate.

[0089] S15. According to the Voce type isotropic hardening model, we can get:

[0090]

[0091] Among them, τ0, τ s , g0 is the material parameter, is the rate of change of hardening modulus, γ is the shear strain, q is the cyclic soft hardening control parameter, β is the reference slip system, and δ is the Kronecker symbol.

[0092] S16. According to the AF type kinematic hardening model, it can be obtained that:

[0093]

[0094] in, is the back stress change rate, C and D are material parameters.

[0095] Step 2, use abaqus software to establish a finite element simulation model and apply boundary conditions;

[0096] The specific process of step 2 is as follows:

[0097] S21. Use optical microscope, scanning electron microscope and electron backscatter microscope (EBSD) to analyze and obtain the grain orientation and grain size of the powder high temperature alloy for the wheel disc, such as Figure 2 shown.

[0098] S22. In dream3D software, import the grain orientation and grain size of the corresponding material, consider both the calculation efficiency and the accuracy of the calculation results, select the finite element model size of 400×400×400μm and the grid unit size of 10μm, and generate the input file of the three-dimensional representative volume unit.

[0099] S23. Integrate and import the input files into abaqus finite element, and use python script to input material parameters and periodic boundary conditions.

[0100] S24, such as Figure 3 As shown, the three-dimensional volume unit X 1 , X 2 , X 3 Three points are fixed and constrained. 4The displacement load corresponding to the cycle is applied to the point, and the cyclic temperature is applied uniformly to the whole model.

[0101] Step 3, obtaining the values ​​of various material parameters in crystal plasticity under thermomechanical fatigue conditions through simulation analysis;

[0102] The specific process of step 3 is as follows:

[0103] S31. According to the thermomechanical fatigue temperature range (500-800°C), five temperatures (500°C, 600°C, 700°C, 750°C, and 800°C) are selected within this temperature range for isothermal fatigue testing. By continuously adjusting various parameters of crystal plasticity, the simulation results at each temperature are compared with the test results at the corresponding temperature until the average error is less than 10%. At this time, each parameter is the crystal plasticity parameter at the corresponding temperature, such as Figure 4 shown.

[0104] S32. In order to obtain the magnitude of the temperature variation of various parameters under thermomechanical fatigue conditions, the elastic tensor C ij Expressed as a function of temperature T:

[0105] E=f(T)

[0106] K ij =C ij / E

[0107] Where E is the elastic modulus, f(T) is the temperature-dependent linear function, and K ij are the parameters obtained by fitting.

[0108] S33. The relationship between the power-rate hardening model parameter n and the temperature T is as follows:

[0109]

[0110] Among them, η f and μ f are parameters related to the elastic tensor, k is the Boltzmann constant, and A2 is the fitting parameter.

[0111] Among the S34 and Voce type anisotropic parameters, the relationship between each parameter and temperature is as follows:

[0112]

[0113] Among them, χ(T), φ(T), and ψ(T) are temperature-related linear functions, which are obtained by fitting. are the material parameters at reference temperature.

[0114] S35. For the back stress parameter C / D, it can also be expressed as an exponential correlation function. The specific formula is as follows:

[0115]

[0116] D=A4exp(υ(T))+B4

[0117] in, υ(T) is also a linear function related to temperature, and A3-A4 and B3-B4 are parameters obtained by fitting.

[0118] S36. The temperature-related crystal plastic material parameters involved in S13-S16 obtained by simulation at different temperatures in S31 are respectively brought into S32-S35 for fitting to obtain the function size of each parameter related to temperature under thermomechanical fatigue conditions.

[0119] Step 4, bring the various crystal plasticity parameters obtained by S36 fitting into the crystal plasticity theory under thermomechanical fatigue derived in S1, and write the corresponding UMAT subroutine in combination with the material grain orientation obtained in S21;

[0120] like Figure 5 As shown, the specific process of step 4 is:

[0121] S41: Since the material used in this method is a powder high-temperature alloy for a wheel disc, and its microstructure is an FCC face-centered cubic unit cell, C 11 , C 12 , C 44 Three parameters describe its elastic deformation behavior. By adjusting these parameters (C 11 , C 12 , C 44 ) can control the elastic segment results of static stretch in the simulation results, such as Figure 6 The static stretching simulation results and experimental results at different temperatures are shown. The static stretching simulation results and experimental results are compared to determine the appropriate value parameters; the initial elastic tensor at the initial temperature is compiled into the UMAT subroutine, and the matrix form is as follows:

[0122]

[0123] S42: Set the time increment step size to 0.01, calculate the strain increment Δε and the local elastic tensor corresponding to the time Δt, and count the magnitude of the slip system direction s and the slip surface normal vector m.

[0124] S43: Through the given C 11 , C 12 , C 44, C, D, n and other initial parameter values, and calculate the initial solution of the shear strain increment Δγ within the time Δt.

[0125] S44: Since the solution of Δγ is the initial solution at this time, it is necessary to use the Newton-Raphson method for iterative calculation. In UMAT, it is determined whether Δγ converges. If not, the material parameters are updated to continue iterative calculation. If converged, the analytical solution size γ is obtained. t+Δt After that, the next time increment t = (1 + n) Δt is entered to continue the calculation until the incremental step reaches the set step size, that is, t = t step Stop calculation.

[0126] Step 5, assign the crystal plastic material parameters under thermomechanical fatigue conditions obtained in step 3 to the model established in step 2 in abaqus, use the UMAT program written in step 4 as the abaqus calculation file, carry out simulation analysis of crystal plastic constitutive under thermomechanical fatigue, and finally compare the simulation results with the experimental results.

[0127] The specific process of step 5 is as follows:

[0128] The parameters of the crystal plastic material under thermomechanical fatigue conditions are assigned to the established model in abaqus, and the UMAT subroutine is written as the calculation basis of abaqus. The UMAT subroutine can fully consider the influence of temperature cycle on the mechanical behavior of the material, and carry out simulation analysis of crystal plastic constitutive under thermomechanical fatigue. The simulation results are compared with the test results. The results are as follows Figure 7 and Figure 8 As shown, Figure 7 This is a comparison chart between IP thermomechanical simulation results and test results, with an average error of about 9.77%; Figure 8 The figure shows the comparison between the OP thermomechanical simulation results and the test results. The average error is about 6.53%, which verifies the accuracy of the simulation results.

[0129] The above is an exemplary description of the present invention in conjunction with the accompanying drawings. It is obvious that the specific implementation of the present invention is not limited to the above-mentioned method. As long as such non-substantial improvements are made by adopting the method concept and technical solution of the present invention, or the concept and technical solution of the present invention are directly applied to other occasions without improvement, they are all within the protection scope of the present invention.

Claims

1. A method for establishing a crystal plasticity constitutive model under thermomechanical fatigue conditions, characterized in that: The steps include: S1. Derive the constitutive theory of crystal plasticity under thermomechanical fatigue; S2, establish a finite element simulation model and apply boundary conditions; S3. Obtain the values ​​of various material parameters in crystal plasticity under thermomechanical fatigue conditions through simulation analysis; S4, based on the crystal plasticity constitutive theory under thermomechanical fatigue derived in step S1, write the corresponding UMAT subroutine; S5. Based on steps S2, S3 and S4, a simulation analysis of crystal plasticity constitutive model under thermomechanical fatigue is carried out, and finally the simulation results are compared with the test results to verify the accuracy of the simulation results; The specific process of step S1 is: S11, deformation gradient F can be decomposed into three parts: elastic deformation gradient, plastic deformation gradient and thermal deformation gradient, namely: F=F e F θ F p where F e is the elastic deformation gradient, F θ is the thermal deformation gradient, F p is the plastic deformation gradient; S12. According to the plastic deformation gradient of the slip system and Schmid's law, we can get: in is the shear strain rate of slip system α, F p-1 is the contravariant tensor, s α is the normal direction of the slip surface of the slip system α, m α is the slip direction of the slip system α; S13. Combined with the thermal expansion coefficient measured in the test, it can be obtained that: Among them, F θ-1 is the contravariant tensor, is the temperature change rate, ρ is the second-order tensor form of the thermal expansion coefficient; S14. According to the power-rate hardening law, we can get: Among them, τ α is the shear stress of the slip system α, X α is the α back stress of the slip system, g α is the α hardening strength of the slip system, is the reference shear strain rate; S15. According to the Voce type isotropic hardening model, we can get: Among them, τ0, τ s , g0 is the material parameter, is the rate of change of hardening modulus, γ is the shear strain, q is the cyclic soft hardening control parameter, β is the reference slip system, and δ is the Kronecker symbol; S16. According to the AF type kinematic hardening model, it can be obtained that: in, is the back stress change rate, C and D are material parameters.

2. The method for establishing a crystal plasticity constitutive model under thermomechanical fatigue conditions according to claim 1, characterized in that: In step S1, three parts, namely, elastic deformation gradient, plastic deformation gradient and thermal deformation gradient, are comprehensively considered.

3. The method for establishing a crystal plasticity constitutive model under thermomechanical fatigue conditions according to claim 1, characterized in that: The specific process of step S2 is: S21. In the dream3D software, import the grain orientation and grain size of the target material, consider both the calculation efficiency and the accuracy of the calculation results, select the finite element model size and the grid unit size, and generate the input file of the three-dimensional representative volume unit; S22, integrate and import the input files into the abaqus finite element, and use the python script to input material parameters and periodic boundary conditions; S23. Apply fixed constraints to the three vertices of the three-dimensional representative volume unit, apply a displacement load corresponding to the cycle to another vertex, and apply a uniformly changing cyclic temperature to the entire model.

4. The method for establishing a crystal plasticity constitutive model under thermomechanical fatigue conditions according to claim 3, characterized in that: At least one of an optical microscope, a scanning electron microscope, and an electron backscatter microscope is used in advance to analyze and obtain the grain orientation and grain size of the target material.

5. The method for establishing a crystal plasticity constitutive model under thermomechanical fatigue conditions according to claim 1, characterized in that: The specific process of step S3 is: S31, according to the thermomechanical fatigue temperature range, perform isothermal fatigue test, by continuously adjusting various parameters of crystal plasticity, compare the simulation results at various temperatures with the test results at corresponding temperatures, until the average error reaches the requirement, at which time each parameter is the crystal plasticity parameter at the corresponding temperature; S32. In order to obtain the magnitude of the temperature variation of various parameters under thermomechanical fatigue conditions, the elastic tensor C ij Expressed as a function of temperature T: E=f(T) K ij =C ij / E Where E is the elastic modulus, f(T) is the temperature-dependent linear function, and K ij are the parameters obtained for the fitting; S33. The relationship between the power-rate hardening model parameter n and the temperature T is as follows: Among them, η f and μ f are parameters related to the elastic tensor, k is the Boltzmann constant, and A2 is the fitting parameter; Among the S34 and Voce type anisotropic parameters, the relationship between each parameter and temperature is as follows: Among them, χ(T), φ(T), and ψ(T) are temperature-related linear functions, which are obtained by fitting. is the material parameter at reference temperature; S35. For the back stress parameter C / D, it can also be expressed as an exponential correlation function. The specific formula is as follows: D=A4exp(υ(T))+B4 in, υ(T) is also a linear function related to temperature, and A3-A4 and B3-B4 are parameters obtained by fitting; S36. Substitute the numerical values ​​of the crystal plastic material parameters obtained by simulation at different temperatures in S31 into S32-S35 for fitting, so as to obtain the function size of each parameter related to temperature under thermomechanical fatigue conditions.

6. The method for establishing a crystal plastic constitutive model under thermomechanical fatigue conditions according to claim 5, characterized in that: In step S31, the condition for the average error to meet the requirement is that the average error is less than 10%.

7. The method for establishing a crystal plasticity constitutive model under thermomechanical fatigue conditions according to claim 1, characterized in that: The specific process of step S4 is: S41. According to the microstructure of the target material, corresponding parameters are used to describe its elastic deformation behavior. By adjusting the values ​​of these parameters, the elastic section results of static stretching in the simulation results are controlled. Static stretching simulations and experiments are performed at different temperatures. The static stretching simulation results and test results are compared to determine appropriate value parameters. The initial elastic tensor at the initial temperature is programmed into the UMAT subroutine; S42, setting the time increment step size, calculating the strain increment Δε and the local elastic tensor corresponding to the time Δt, and counting the slip system direction s and the slip surface normal vector m; S43, calculating the initial solution of the shear strain increment Δγ within the time Δt by using the given initial parameter values; S44, use the Newton-Raphson method to perform iterative calculations, and determine whether Δγ converges in UMAT. If not, update the material parameters and continue the iterative calculations; if converged, obtain the analytical solution size γ t+Δt After that, the next time increment t = (1 + n) Δt is entered to continue the calculation until the incremental step reaches the set step size, that is, t = t step Stop calculation.

8. The method for establishing a crystal plastic constitutive model under thermomechanical fatigue conditions according to claim 1, characterized in that: The specific process of step S5 is: The crystal plastic material parameters under the thermomechanical fatigue conditions in step S3 are assigned to the model established in step S2 in abaqus. Combined with the UMAT subroutine written in step S4 as the calculation basis of abaqus, a simulation analysis of the crystal plastic constitutive under thermomechanical fatigue is carried out. The simulation results are compared with the experimental results to verify the accuracy of the simulation results.

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